When science meets marketing: Daniel Gilbert, CEO and Founder, of Brainlabs reveals the winning formula for driving growth, results and business success for Deliveroo – powered by a unique combination of Google Ads and an automated bidding strategy.

Google Ads1 is seen as a relatively mature platform in some people’s eyes and yet last year by some estimates, there were a thousand different changes to Google’s advertising platform. That’s an insane rate of development for a supposedly ‘mature product’. And all that means is that there are opportunities for me and all the people that I work with to continuously learn.

As a PPC agency and technology provider, we are often presented with situations where a client’s needs require more than the default capabilities of Google Ads.

Deliveroo is a great example. They needed a bidding model that could be applied to over three million keywords, with accounts across four countries, two continents and four different languages. To add further complexity, we would need to segment keywords according to campaigns (in the 100,000s) and factor in location, time of day, demographics, and device.

“Within a year, Deliveroo were able to increase their Google Ads budget by more than 100x – a remarkable period of growth, enabled by an automated bidding strategy.”

– Dan Gilbert, CEO and Founder, Brainlabs

Here’s how we did it

We needed to model user behaviour, taking into account cost, clicks, conversions, time of day, device and even the weather. Google Ads has something called Bid Simulator, which provides a set of CPC bids for certain keywords and the expected number of clicks one can expect for that bid. Unfortunately, Google Ads only offers these predictions for a fixed number of discrete CPC bids. In order to give our algorithm flexibility, we interpolated between these data points to model conversions at any CPC bid in a given range, not just at the suggested points.

Deliveroo wanted to drive mobile conversions, so it was crucial to analyse changes in user behaviour according to device. To add further precision to our model, we used Bayesian statistics (making predictions based on prior distributions) to model bid levels for device and time of day. This meant we could optimise bids using not just conversion rate data, but also CPC and CPA data. There’s no point having high bids when there’s no volume but high conversion rates, say at 4am on desktop. Likewise it would be catastrophic to lower bids at 5pm on a mobile, when conversion rates are lower but orders are still high.

We then used bid simulator to extrapolate the effect of the bid changes on clicks, cost, and conversions by device. This is the final piece in the jigsaw as it meant we could pick bids at any reasonable value and fine-tune things more precisely, as well as adjust the model based on budgetary constraints and CPA targets.

Because we needed to change bids promptly on the hour for the 100,000+ Deliveroo campaigns with no compromises, we quickly hit the Google-imposed execution limits for the Google Ads API. In order to get around this, we constructed the tool on a framework of computer clusters. In this way we got around the API limits and were able to increase the possible number of executions by up to 14 times, giving us a total throughput of 1,400 executions per second.

The results were incredible. Within a year, Deliveroo were able to increase their Google Ads budget by more than 100x – a remarkable period of growth, enabled by an automated bidding strategy.

What’s great about Google Ads is that its API is so accessible that it encourages this sort of innovation. I’m excited to see what’s next.